A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

An investigation into the cause of loss of containment from the supply of mini-bulk lubricants

An Intermediate Bulk Container (IBC) was punctured during its handling, releasing oil onto soil at an environmentally-sensitive region of Australia. The telehandler did not pierce the plastic of the IBC directly (as was expected) but rather one of the tynes had caught on the underside of the metal base plate, despite numerous controls being in place at time of spill, revealing a previously unreported mechanism for a fluid spill from handling of petroleum hydrocarbons. The diverse investigation team used a root cause analysis (RCA) technique to identify the underlying cause: the inspection process was inadequate with contributing factors of not using a spotter and design of IBC did not anticipate conditions. Engineering controls were put in place as part of the change management process to help prevent spills from occurring from piercing from telehandler tynes on the current project site.     

Strain engineering for thermal conductivity of single-walled carbon nanotube forests

We perform classical molecular dynamics simulations to investigate the mechanical compression effect on the thermal conductivity of the single-walled carbon nanotube (SWCNT) forest, in which SWCNTs are closely aligned and parallel with each other. We find that the thermal conductivity can be linearly enhanced by increasing compression before the buckling of SWCNT forests, but the thermal conductivity decreases quickly with further increasing compression after the forest is buckled. Our phonon mode analysis reveals that, before buckling, the smoothness of the inter-tube interface is maintained during compression, and the inter-tube van der Waals interaction is strengthened by the compression. Consequently, the twisting-like mode (good heat carrier) is well preserved and its group velocity is increased by increasing compression, resulting in the enhancement of the thermal conductivity. The buckling phenomenon changes the circular cross section of the SWCNT into ellipse, which causes effective roughness at the inter-tube interface for the twisting motion. As a result, in ellipse SWCNTs, the radial breathing mode (poor heat carrier) becomes the most favorable motion instead of the twisting-like mode and the group velocity of the twisting-like mode drops considerably, both of which lead to the quick decrease of the thermal conductivity with further increasing compression after buckling.     

Characteristic of polysaccharides from Flammulina velutipes in vitro digestion under salivary,simulated gastric and small intestinal conditions and fermentation by human gut microbiota

In this study, in vitro digestion and fermentation of Flammulina velutipes -derived polysaccharides (FVP) were investigated. It was found that FVP mainly consisted of 48.45% glucose, 15.40% mannose, 14.60% xylose, 11.80% fucose and 9.90% galactose. The -human saliva, simulated gastric and small intestinal juices conditions did not break down the FVP. Based on in vitro fermentation tests, FVP modulated the composition of gut microbiota by elevating the amounts of Bifidobacteriaceae and Bacteroidaceae and reducing the numbers of genera Lachnospiraceae and Enterococcaceae. Meanwhile, FVP affected the synthesis of short-chain fatty acids derived from gut microbiota.     

Unusual Two-Step Assembly of a Minimalistic Dipeptide-Based Functional Hypergelator

Self-assembled peptide hydrogels represent the realization of peptide nanotechnology into biomedical products. There is a continuous quest to identify the simplest building blocks and optimize their critical gelation concentration (CGC). Herein, a minimalistic, de novo dipeptide, Fmoc-Lys(Fmoc)-Asp, as an hydrogelator with the lowest CGC ever reported, almost fourfold lower as compared to that of a large hexadecapeptide previously described, is reported. The dipeptide self-assembles through an unusual and unprecedented two-step process as elucidated by solid-state NMR and molecular dynamics simulation. The hydrogel is cytocompatible and supports 2D/3D cell growth. Conductive composite gels composed of Fmoc-Lys(Fmoc)-Asp and a conductive polymer exhibit excellent DNA binding. Fmoc-Lys(Fmoc)-Asp exhibits the lowest CGC and highest mechanical properties when compared to a library of dipeptide analogues, thus validating the uniqueness of the molecular design which confers useful properties for various potential applications.     

Fabrication and microwave absorption properties of magnetite nanoparticle–carbon nanotube–hollow carbon fiber composites

Absorbents with “tree-like” structures, which were composed of hollow porous carbon fibers (HPCFs) acting as “trunk” structures, carbon nanotubes (CNTs) as “branch” structures and magnetite (Fe₃O₄) nanoparticles playing the role of “fruit” structures were prepared by chemical vapor deposition technique and chemical reaction. Microwave reflection loss, permittivity and permeability of Fe₃O₄–CNTs–HPCFs composites were investigated in the frequency range of 2–18 GHz. It was proven that prepared absorbents possessed the excellent electromagnetic wave absorbing performances. The bandwidth with a reflection loss less than −15 dB covers a wide frequency range from 10.2 to 18 GHz with the thickness of 1.5–3.0 mm, and the minimum reflection loss is −50.9 dB at 14.03 GHz with a 2.5 mm thick sample layer. Microwave absorbing mechanism of the Fe₃O₄–CNTs–HPCFs composites is concluded as dielectric polarization and the synergetic interactions exist between Fe₃O₄ and CNTs–HPCFs.     

Effect of structure on the properties of polyurethanes based on aromatic cardanol-based polyols prepared by thiol-ene coupling

Industrial-grade cardanol and 2-mercaptoethanol were reacted to generate hydroxyl-functionalized cardanol by UV, free-radical-initiated thiol-ene coupling between the double bond moieties of the cardanol long carbon side chain and thiol functional groups. The average hydroxyl number of the hydroxyl-functionalized cardanol was controlled by reaction time, with the hydroxyl values of this ranging within 168–201 mg KOH g⁻¹. This cardanol was then used as a polyol to prepare cardanol-based polyurethane with hexamethylene diisocyanate and a NCO/OH ratio of 1. To compare the effect of cardanol-based polyols with the properties of cardanol-based polyurethane, cardanol modified with 10-undecylenate was used as a raw material to prepare cardanol-based polyols, including the long carbon chain of 10-undecylenate. All properties were examined, and data revealed that cardanol-based polyols including this long carbon chain can improve the hydrophobic and mechanic properties of the cardanol-based polyurethane.     

A novel intelligent approach for yaw position forecasting in wind energy systems

Yaw control systems orientate the rotor of a wind turbine into the wind direction, optimize the wind power generated by wind turbines and alleviate the mechanical stresses on a wind turbine. Regarding the advantages of yaw control systems, a k-nearest neighbor classifier (k-NN) has been developed in order to forecast the yaw position parameter at 10-min intervals in this study. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters are used in 2, 3, 4, 5 and 6-dimensional input spaces. The forecasting model using Manhattan distance metric for k = 3 uncovered the most accurate performance for atmosphere pressure, wind direction, wind speed and rotor speed inputs. However, the forecasting model using Euclidean distance metric for k = 1 brought out the most inconsistent results for atmosphere pressure and wind speed inputs. As a result of multi-tupled analyses, many feasible inferences were achieved for yaw position control systems. In addition, the yaw position forecasting model developed was compared with the persistence model and it surpassed the persistence model significantly in terms of the improvement percent.